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2017 • Conference Paper

A robust convex optimization framework for autonomous network planning under load uncertainty

Authors:
Martin, Benoît, Glineur, François , De Jaeger, Emmanuel
Published in:
Proceedings of 2017 IEEE Manchester PowerTech

Volume: 2017

Autonomous microgrid planning is a Mixed-Integer Non Convex decision problem that requires to consider investments in both distribution and generation capacity and represents significant computation challenges. We proposed in a previous publication a deterministic Second-Order Cone (SOC) relaxation of this problem that made it computationally tractable for real-size cases. However, this problem is subject to considerable uncertainty emanating from load consumption, RES-based generation and contingencies. In this paper, we thus present a robust optimization approach that extends our previous work by including load related uncertainty at the cost of a substantial increase of the computational burden. The results show that significantly higher investment and operational costs are incurred to account for the load related uncertainty.

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